UC Berkeley News


New campus center to develop mathematical model of brain
Funded by handheld-computing pioneer, Redwood Center for Theoretical Neuroscience will advance 'data-rich, theory-poor' field

| 12 October 2005

Jeff Hawkins, creator of the first commercially successful handheld computer, has endowed a new Berkeley research center to develop mathematical and computational models of how the brain works. The Redwood Center for Theoretical Neuroscience will operate within the Helen Wills Neuroscience Institute.

Hawkins, who attended the graduate program in biophysics at Berkeley nearly 20 years ago to pursue his interest in neuroscience, later co-founded Palm Computing and Handspring, introducing the very successful PalmPilot and Treo product lines. He also co-authored the well-received book On Intelligence.

Bruno Olshausen (Jock Hamilton photo)
Three years ago, Hawkins again turned his attention to neuroscience with the founding of the Redwood Neuroscience Institute (RNI) in Menlo Park. The new Redwood Center at Berkeley is being funded by a $4-million gift from Hawkins and his wife, Janet Strauss. Bruno Olshausen, formerly of RNI, will become an associate professor of neuroscience at Berkeley and head of the new center.

"There is a natural affinity between the RNI and the Wills Institute," Olshausen says. He and his team will pursue similar research goals here, attempting to create a model of the brain that can be tested in the lab and eventually mimicked by a computer.

"Our goal is to develop a theoretical framework for the neocortex - the outer layer of the brain involved in conscious perception and action," says Olshausen. "There is no good framework now, despite tons of data. The field is data-rich but theory-poor."

Robert Knight, a professor of psychology and of neuroscience and director of the Wills Institute, praised Olshausen and Hawkins as "guys who don't just come up with unrestrained theory. They build theory based on known observations, anatomically or physiologically." Olshausen, for example, originated a theory called "sparse coding" in the late 1990s, proposing that the brain operates with the least number of neurons possible.

He currently is interested in how the visual area of the brain encodes images that allow us to recall and recognize them in an instant, despite different orientations and different lighting.

"If you look at and recognize a pencil, then re-orient it, it's still a pencil," he says. "From a computational point of view, thinking of a pencil as a bunch of pixels, it's an immense challenge to understand. Yet somehow, in humans, it's done naturally. How does this happen?"

The much-touted area of artificial intelligence tried to solve problems such as this, too, but without reference to the way the brain does it. The area of cognitive science tries to bring psychology to bear on the question, creating mathematical models based on behavior.

Olshausen and his colleagues, however, want to understand the cortex at a level closer to the individual nerve cell, so as to explain things such as memory, sensory motor function, and attention.

"We're trying to drive down to the neurobiological sub-unit, including the individual nerve cell," he says. "If we are successful, we should be able to produce a theory that is testable by neurobiologists recording at the level of individual neurons, thereby relating neural activity to perceptual function."

The theories also can be tested on live volunteers using the Wills Institute's functional magnetic resonance imager. Other areas of interest among the six researchers in the center are how the sensory world is encoded in the brain, how memories are stored, and how the brain synchronizes activity.

As far as Hawkins is concerned, understanding of the neocortex is already at a level where it's possible to create software inspired by the algorithms of the brain, and therefore train computers to do things we would label as intelligent. He is putting his beliefs into action with the founding of Numenta, which is developing a new type of computer-memory system modeled after the human neocortex.

"When it comes to looking at pictures, and saying, 'What is in this image? What am I looking at?' - there is no computer that can do that today," he says. "There is no computer that can listen to speech or read text and understand what is being spoken about. Numenta's technology can do that. There are no good algorithms for general-purpose robotics, how to make a machine that can walk around in a fluid way, not like some lumbering zombie. Insects do it, mice do it, humans do it - we don't know how to do that. Numenta's technology can do that.

"More importantly, the technology can do a lot of things humans don't do well," he continues. "It can understand complex worlds and make predictions about them, and that is the core of what intelligence is all about - forming an understanding about a world and then predicting the future. We have a fundamental technology, which is basically brains, intelligence, and the neocortex, but the most interesting applications will be ones that are hard to think of now."

He stresses, however, that the new Redwood Center has many challenges ahead in fleshing out the theories he's taking to the computer design board.
"There is a lot of work still to be done, mapping the theory to the biology and understanding exactly how the biology produces these things," he says. "And that is going to continue. Yet I have enough now to start a business that builds the technology side of it. The Redwood Center is going to continue doing the neuroscience aspect of cortical theory."

Aside from cortical theory, however, Knight emphasizes that the center will help researchers across the campus by providing novel computational and theoretical perspectives to better understand the massive data sets generated today by studies of the brain. Handling monstrous data sets and extracting information from them requires sophistication in both computation and brain theory.

"There are so many ways to look at complex physiological data," he says. "You have to have people who are mathematically sophisticated, and you have to have people who have thought about the theory and how the brain might actually use different patterns of neural firing to produce behavior. It's really not the computer so much: it's more how you understand the problem and extract the signal from the noise and verify that it's real. That's where it takes computationally and theoretically savvy people to make a difference."

The founding of the new Redwood Center was celebrated on Friday, Oct. 7, with a daylong symposium at the Faculty Club.